EIS: using the metadatabase approach for data integration and OLAP.

Abstract

by Ho Kwok-Wai.Thesis (M.Phil.)--Chinese University of Hong Kong, 1998.Includes bibliographical references (leaves 121-126).Abstract also in Chinese.ABSTRACT --- p.IITABLE OF CONTENTS --- p.VLIST OF FIGURES --- p.XACKNOWLEDGMENTS --- p.XIIChapter CHAPTER 1 --- INTRODUCTION --- p.1Chapter 1.1 --- Need support in data integration --- p.2Chapter 1.2 --- Need support in On-line Analytical Processing (OLAP) --- p.4Chapter 1.3 --- The proposed research --- p.5Chapter 1.4 --- Scope of the study --- p.6Chapter 1.5 --- Organization of the Thesis --- p.7Chapter CHAPTER 2 --- LITERATURE REVIEW --- p.8Chapter 2.1 --- Executive Information System (EIS) --- p.9Chapter 2.1.1 --- Definition --- p.9Chapter 2.1.2 --- Goals of Executive Information System --- p.10Chapter 2.1.3 --- Role of Executive Information System --- p.11Chapter 2.1.4 --- General characteristics of Executive Information System --- p.12Chapter 2.1.4.1 --- A separate executive database --- p.12Chapter 2.1.4.2 --- Data aggregation facilities --- p.12Chapter 2.1.4.3 --- Drill-Down (and Roll-Up) --- p.13Chapter 2.1.4.4 --- Trend analysis --- p.13Chapter 2.1.4.5 --- Highly user-friendly interfaceChapter 2.1.4.6 --- Flexible menu-based data retrieval --- p.14Chapter 2.1.4.7 --- High quality of business graphics --- p.14Chapter 2.1.4.8 --- Simple modeling facilities --- p.15Chapter 2.1.4.9 --- Communications --- p.15Chapter 2.1.4.10 --- Automated links to other databases --- p.15Chapter 2.1.4.11 --- Briefing book --- p.16Chapter 2.1.5 --- Architecture of Executive Information System --- p.16Chapter 2.1.6 --- Potential problems of Executive Information System --- p.18Chapter 2.2 --- On-line Analytical Processing (OLAP) --- p.20Chapter 2.2.1 --- Limitations of OLAP --- p.21Chapter 2.2.2 --- Integration of heterogeneous distributed systems and databases --- p.21Chapter 2.3 --- Data Warehousing (DW) --- p.23Chapter 2.3.1 --- Definition --- p.24Chapter 2.3.1.1 --- Subject-Orientation --- p.24Chapter 2.3.1.2 --- Integration --- p.25Chapter 2.3.1.3 --- Time Variancy --- p.26Chapter 2.3.1.4 --- Nonvolatile --- p.27Chapter 2.3.2 --- Goal of Data Warehousing --- p.28Chapter 2.3.3 --- Architecture of Data Warehousing --- p.28Chapter 2.3.3.1 --- Integrator --- p.29Chapter 2.3.3.2 --- Monitor --- p.30Chapter 2.3.3.3 --- Data Warehouse --- p.31Chapter 2.3.4 --- Application in EIS --- p.31Chapter 2.3.5 --- Problems associated with Data Warehouse --- p.33Chapter 2.4 --- The Metadatabase Approach --- p.35Chapter 2.4.1 --- Goals of the Metadatabase Approach --- p.36Chapter 2.4.2 --- Structure of the Metadatabase Approach --- p.37Chapter 2.4.3 --- Metadatabase Approach functionalities --- p.40Chapter 2.4.4 --- TSER Modeling Technique --- p.42Chapter 2.4.4.1 --- The Functional Model --- p.43Chapter 2.4.4.1.1 --- Subject --- p.43Chapter 2.4.4.1.2 --- Context --- p.43Chapter 2.4.4.2 --- The Structural Model --- p.44Chapter 2.4.4.2.1 --- Entity --- p.44Chapter 2.4.4.2.2 --- Plural Relationship (PR) --- p.45Chapter 2.4.4.2.3 --- Functional Relationship (FR) --- p.45Chapter 2.4.4.2.4 --- Mandatory Relationship (MR) --- p.45Chapter 2.4.4.3 --- Metadatabase Repository --- p.46Chapter CHAPTER 3 --- RESEARCH METHODOLOGY --- p.48Chapter 3.1 --- Literature review --- p.49Chapter 3.2 --- Architecture construction --- p.50Chapter 3.3 --- Algorithm and methods development --- p.50Chapter 3.4 --- Prototyping --- p.51Chapter 3.5 --- Analysis and evaluation --- p.51Chapter CHAPTER 4 --- MULTIDIMENSIONAL DATA ANALYSIS --- p.53Chapter 4.1 --- Multidimensional Analysis Unit (MAU) --- p.54Chapter 4.2 --- New steps for multidimensional data analysis --- p.57Step 1 Indicator Selection --- p.57Step 2 Dimensions Determination --- p.58Step 3 Dimensions Selection --- p.58Step 4 MAU Sub-view Materialization --- p.59Step 5 On-line Analytical Processing (OLAP) --- p.59Chapter CHAPTER 5 --- NEW ARCHITECTURE FOR EXECUTIVE INFORMATION SYSTEM --- p.60Chapter 5.1 --- Evolution of EIS architecture --- p.60Chapter 5.2 --- Objectives of the new EIS architecture --- p.63Chapter 5.3 --- The new EIS architecture --- p.65Chapter 5.3.1 --- The Metadatabase Management System (MDBMS) --- p.67Chapter 5.3.2 --- The ROLAP/MDB Interface --- p.68Chapter 5.3.2.1 --- The Indicator Browser --- p.69Chapter 5.3.2.2 --- The Dimension Selector --- p.70Chapter 5.3.2.3 --- The Multidimensional Data Analyzer --- p.70Chapter 5.3.3 --- The ROLAP/MDB Analyzer --- p.71Chapter 5.3.3.1 --- The Dimension Determination Module --- p.71Chapter 5.3.3.2 --- The MAU Schema Saver --- p.72Chapter 5.3.3.3 --- The MQL Generator --- p.72Chapter 5.3.3.4 --- The MAU Sub-view Materializer --- p.72Chapter 5.3.3.5 --- The ROLAP/MDB Processor --- p.73Chapter CHAPTER 6 --- ALGORITHM AND METHODS FOR THE NEW EIS ARCHITECTURE.… --- p.74Chapter 6.1 --- Indicator Browser --- p.74Chapter 6.2 --- Determining dimensions and storing MAU Schema --- p.77Chapter 6.3 --- Dimensions selection --- p.82Chapter 6.4 --- Materialize MAU Sub-view --- p.82Chapter 6.5 --- Multidimensional data analysis in relational manner --- p.85Chapter 6.5.1 --- SQL statements for three dimensional slide operation --- p.87Chapter 6.5.2 --- SQL statements for n-dimensional slide operation --- p.89Chapter 6.5.3 --- SQL statements for n-dimensional dice operation --- p.91Chapter 6.5.4 --- Rotation --- p.92Chapter 6.5.5 --- Drill-Down (and Roll-Up) --- p.94Chapter CHAPTER 7 --- A CASE STUDY USING THE PROTOTYPED EIS --- p.97Chapter 7.1 --- A Business Case --- p.97Chapter 7.2 --- Multidimensional data analysis --- p.98Step 1 Indicator selection --- p.99Step 2 & 3 Dimension determination & MAU Schema storage --- p.100Step 4 Dimension specification --- p.102Step 5 MAU Sub-view formation --- p.104Step 6 Multidimensional data analysis operations --- p.104Chapter CHAPTER 8 --- EVALUATION OF THE NEW EIS ARCHITECTURE --- p.110Chapter 8.1 --- Improvements --- p.110Chapter 8.1.1 --- Adaptability --- p.111Chapter 8.1.2 --- Flexibility --- p.112Chapter 8.2 --- New features of the new EIS architecture --- p.113Chapter 8.2.1 --- Access on-line production data --- p.113Chapter 8.2.2 --- Facilitate data-mining --- p.114Chapter 8.3 --- Processing efficiency problem --- p.114Chapter 8.3.1 --- MAU Schema Saver for reusability --- p.115Chapter 8.3.2 --- Dimension Selector to scale down data retrieval --- p.116Chapter 8.3.3 --- MAU Sub-view materialization for reusability --- p.116Chapter 8.3.4 --- Incorporate data warehouse to reduce access to local systems --- p.117Chapter 8.4 --- Summary --- p.117Chapter CHAPTER 9 --- CONCLUSION --- p.118Chapter CHAPTER 10 --- DIRECTION OF FUTURE STUDIES --- p.120REFERENCES --- p.121APPENDIX --- p.127Global Information Resources Dictionary (GIRD) --- p.12